running-the-proxy

running-the-proxy is a skill for Claude Code from xberg-io/liter-llm. It costs 50 tokens per session (543 once invoked), scanned A, original, MIT.

Instructions for running liter-llm api, a gateway that accepts requests in the same format as the OpenAI API and sends them to configured language-model providers. It covers virtual keys, rate limits, budgets, cost tracking, and model routing.

In plain words
What is it for?
Start the gateway, configure models and virtual keys, set request and token limits, apply budgets, track costs, and send chat-completion requests.
Why use it?
It explains how to operate one gateway for multiple users and model providers while controlling access and spending. Environment variables can keep API secrets out of the configuration file.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the liter-llm plugin — 7 skills, 1 MCP server shipped together

Good fit Start the gateway, configure models and virtual keys, set request and token limits, apply budgets, track costs, and send chat-completion requests.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xberg-io/liter-llm/running-the-proxy
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add xberg-io/liter-llm --skill running-the-proxy
Clone the repo
git clone --depth 1 https://github.com/xberg-io/liter-llm

Made for: Claude Code.

Or install liter-llm, the plugin that ships this one along with the rest of its 7 skills, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for running-the-proxy

README.md
[![agentmods](https://agentmods.dev/badge/skills/xberg-io/liter-llm/running-the-proxy/github.svg)](https://agentmods.dev/skills/xberg-io/liter-llm/running-the-proxy)
Your own site
<a href="https://agentmods.dev/skills/xberg-io/liter-llm/running-the-proxy"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/running-the-proxy/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for running-the-proxy

Your own site · 80×15
<a href="https://agentmods.dev/skills/xberg-io/liter-llm/running-the-proxy"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/running-the-proxy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 543 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 55
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium MCP Rug Pull · line 67
    Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.
    Fix: Pin the image: image:tag or image@sha256:abc123
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.00543
Opus 5 $0.00025 $0.00271
Sonnet 5 $0.00010 $0.00109
Haiku 4.5 $0.00005 $0.00054

Measured 9d ago against content hash 1b8d61b0814d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

running-the-proxy scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl http://localhost:4000/v1/chat/completions \
plugin/.ai-rulez/skills/running-the-proxy/SKILL.md · 68 lines

What it actually says

Running the Proxy

liter-llm api is a drop-in OpenAI-compatible gateway: 22 REST endpoints that route to 165 providers, with multi-tenant virtual keys, rate limits, budgets, and cost tracking.

Start it

liter-llm api --config liter-llm-proxy.toml

The proxy auto-discovers liter-llm-proxy.toml in the current directory.

Configuration

[server]
host = "0.0.0.0"
port = 4000

[general]
master_key = "${LITER_LLM_MASTER_KEY}"

# Each [[models]] entry maps a routable name to a provider/model and its key.
[[models]]
name = "gpt-4o"
provider_model = "openai/gpt-4o"
api_key = "${OPENAI_API_KEY}"

[[models]]
name = "claude-sonnet"
provider_model = "anthropic/claude-sonnet-4-20250514"
api_key = "${ANTHROPIC_API_KEY}"

# Virtual keys scope which configured model names a caller may use.
[[keys]]
key = "sk-team-frontend"
models = ["gpt-4o", "claude-sonnet"]
rpm = 60
tpm = 100000
budget_limit = 50.0

${ENV_VAR} interpolation keeps secrets out of the file.

Call it like OpenAI

curl http://localhost:4000/v1/chat/completions \
  -H "Authorization: Bearer sk-team-frontend" \
  -d '{"model": "gpt-4o", "messages": [{"role": "user", "content": "Hello"}]}'

Notes

  • Virtual keys scope which models a caller may use and carry their own RPM/TPM and budget limits; the master_key administers them.
  • The OpenAPI 3.1 spec is served at /openapi.json.
  • Endpoints cover chat, embeddings, images, audio, moderations, files, batches, responses, and model listing.
  • Docker: docker run -p 4000:4000 -e LITER_LLM_MASTER_KEY=sk-key ghcr.io/xberg-io/liter-llm.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 68 lines · 50 tokens per session scan A 1b8d61b0814d

Subscribe to this mod's changes

running-the-proxy is a skill published in the GitHub repository xberg-io/liter-llm (252 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 543 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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